# Copyright (c) 2025 Intel Corporation
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#      http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from collections import deque

import openvino as ov

from nncf.common.factory import ModelTransformerFactory
from nncf.common.graph.graph import NNCFGraph
from nncf.common.graph.graph import NNCFNode
from nncf.common.graph.transformations.layout import TransformationLayout
from nncf.common.quantization.quantizer_propagation.structs import QuantizationTrait
from nncf.openvino.graph.metatypes.groups import FAKE_QUANTIZE_OPERATIONS
from nncf.openvino.graph.metatypes.openvino_metatypes import OVReadValueMetatype
from nncf.openvino.graph.transformations.command_creation import OVCommandCreator
from nncf.openvino.quantization.default_quantization import DEFAULT_OV_QUANT_TRAIT_TO_OP_DICT


def remove_fq_from_inputs(model: ov.Model, graph: NNCFGraph) -> ov.Model:
    """
    This method removes the activation Fake Quantize nodes from the model.
    It's needed for the further bias shift calculation that relates on quantized weights.

    :param model: ov.Model instance.
    :param graph: NNCFGraph instance.
    :return: ov.Model instance without activation Fake Quantize nodes.
    """
    transformation_layout = TransformationLayout()
    model_transformer = ModelTransformerFactory.create(model)

    seen_nodes = []
    nodes_queue = deque(graph.get_input_nodes())
    while nodes_queue:
        current_node = nodes_queue.popleft()
        current_node_name = current_node.node_name

        if current_node_name in seen_nodes:
            continue

        seen_nodes.append(current_node_name)
        if current_node.metatype in FAKE_QUANTIZE_OPERATIONS:
            command = OVCommandCreator.create_command_to_remove_quantizer(current_node)
            transformation_layout.register(command)
        nodes_queue.extend(graph.get_next_nodes(current_node))

    return model_transformer.transform(transformation_layout)


def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> list[NNCFNode]:
    """
    Get a list of NNCFNodes to use as start nodes for activation path tracing.

    :param nncf_graph: NNCFGraph to work with.
    :return: Target NNCFGraph input nodes.
    """
    return (
        nncf_graph.get_input_nodes()
        + nncf_graph.get_nodes_by_metatypes([OVReadValueMetatype])
        + nncf_graph.get_nodes_by_metatypes(
            DEFAULT_OV_QUANT_TRAIT_TO_OP_DICT[QuantizationTrait.OUTPUT_QUANTIZATION_AS_WEIGHTS]
        )
    )


def remove_friendly_name_duplicates(model: ov.Model) -> ov.Model:
    """
    Removes duplicates of node names (friendly_name attribute) in the model.

    :param model: ov.Model instance to update.
    :return: Updated ov.Model without duplicated names.
    """
    rt_info_path = ["nncf", "friendly_names_were_updated"]
    friendly_names_flag = "True"
    if model.has_rt_info(rt_info_path) and model.get_rt_info(rt_info_path).value == friendly_names_flag:
        return model

    existing_names = set()
    for op in model.get_ops():
        friendly_name = op.get_friendly_name()
        if friendly_name in existing_names:
            friendly_name = friendly_name + "0"
            op.set_friendly_name(friendly_name)
        existing_names.add(friendly_name)
    model.set_rt_info(friendly_names_flag, rt_info_path)
    return model


def model_has_state(model: ov.Model) -> bool:
    """
    Returns True if model has state else False

    :param model: OpenVINO model
    :return: True if model has state else False
    """
    return len(model.get_sinks()) > 0


def copy_rt_info(model_source: ov.Model, model_dest: ov.Model, path: list[str]) -> None:
    """
    Checks and copies the rt_info from the source to destination model.

    :param model_source: ov.Model instance to copy rt_info from.
    :param model_dest: ov.Model instance to copy rt_info to.
    :param path: Path to rt_info.
    """
    if model_source.has_rt_info(path):
        source_rt_info = model_source.get_rt_info(path)
        model_dest.set_rt_info(source_rt_info, path)
